Abstract: In variants, a method for robotic process automation (RPA) includes: receiving an automation request; optionally determining an application representation of an application associated with the automation request; generating a set of tasks based on the automation request; optionally classifying each task in the set of tasks; generating a set of instructions for each task in the set of tasks; optionally validating the set of instructions; and optionally executing the set of instructions cooperatively forming an RPA bot.

Abstract: A task execution method using resources includes receiving an execution request for a first task; analyzing the first task and dividing the first task into a plurality of sub-tasks; identifying a sub-task using a first neural network from among the sub-tasks and dividing the identified sub-task into a plurality of layer tasks corresponding to calculations between layers constituting the first neural network; calculating a deadline time of each of the sub-tasks; scheduling a first sub-task to be scheduled to a first resource group from among the resources; and, when a runtime of the first sub-task exceeds a deadline time of the first sub-task, scheduling a sub-task or a layer task subsequent to the first sub-task to a second resource group.

Abstract: A determination is made as to whether a value of a first parameter of a first application is to be obtained using a natural language interaction. Based on received input, a first service of a plurality of services is identified. The first service is to be used to perform a first task associated with the first parameter. Portions of the first application to determine the value of the first parameter and to invoke the first service are generated.

Abstract: Multi-cloud deployment strategy is based on automated analysis of context and requirements for an activity workload. The activity workload is defined by user input including information regarding project cost, performance requirements, and geographical preferences. Selection of cloud-based resources for handling the activity workload is based in part on service availability record, projected cost of resources, and physical geographic locations. A cloud services registry provides cloud service provider data for selection to perform aspects of the activity workload.

Abstract: In accordance with embodiments disclosed herein, there are provided mechanisms and methods for automating deployment of applications in a multi-tenant database environment. For example, in one embodiment, mechanisms include managing a plurality of machines operating as a machine farm within a datacenter by executing an agent provisioning script at a control hub, instructing the plurality of machines to download and instantiate a lightweight agent; pushing a plurality of URL (Uniform Resource Locator) references from the control hub to the instantiated lightweight agent on each of the plurality of machines specifying one or more applications to be provisioned and one or more dependencies for each of the applications; and loading, via the lightweight agent at each of the plurality of machines, the one or more applications and the one or more dependencies for each of the one or more applications into memory of each respective machine.

Abstract: A computer system, processor, programming instructions and/or method for balancing the workload of processing pipelines that includes an execution slice, the execution slice comprising at least two processing pipelines having one or more execution units for processing instructions, wherein at least a first processing pipeline and a second processing pipeline are capable of executing a first instruction type; and an instruction decode unit for decoding instructions to determine which of the first processing pipeline or the second processing pipeline to execute the first instruction type. The processor configured to calculate at least one of a workload group consisting of: the first processing pipeline workload, the second processing pipeline workload, and combinations thereof; and select the first processing pipeline or the second processing pipeline to execute the first instruction type based upon at least one of the workload group.

Abstract: A computer system executes a database management system (DBMS). The DBMS manages a database comprised of DBMS resources. The DBMS receives a request to be executed. The request is a DBMS action to be executed using the DBMS resources. The request includes a predicate specifying a maximum cost for executing the request, and a deadline, specifying a deadline by which the request is to be completed in its execution. The DBMS determines a plurality of workloads under which the request is qualified to execute. Each workload of the plurality of workloads includes a respective set of requests that have common characteristics. Each workload of the plurality of workloads includes a respective cost criterion and a respective elapsed time criterion. The DBMS selects a selected workload from among the plurality of workloads. The selected workload has a selected cost criterion and a selected elapsed time criterion. The DBMS begins execution of the request using the selected workload.

Abstract: A virtualization infrastructure control apparatus (10) includes an operation parameter monitoring unit (122) configured to acquire an operation parameter, a resource monitoring unit (121) configured to acquire predetermined load information, and a migration determination unit (111). The migration determination unit (111) determines to execute live migration when the migration determination unit (111) determines that the operation parameter satisfies a predetermined operation condition and that a load is low by comparing a predetermined load information with a predetermined threshold, whereas the migration determination unit (111) determines to execute healing when the migration determination unit (111) determines that the operation parameter does not satisfy the predetermined operation condition or that the load is high by comparing the predetermined load information with the predetermined threshold.

Abstract: A system can determine to restore a datacenter that comprises a group of virtualized workloads. The system can determine respective associations between respective virtualized workloads and respective datastores. The system can determine to restore a first virtualized workload of the group of virtualized workloads first. The system can restore a first portion of infrastructure that corresponds to the first virtualized workload first among a group of infrastructure. The system can, after restoring the first portion of infrastructure, restore a first portion of data that corresponds to the first virtualized workload first among a group of data. The system can, after restoring the first portion of data, restore a first portion of a virtualization layer that corresponds to the first virtualized workload first among a group of virtualization layers. The system can, after restoring the first portion of the virtualization layer, restore the first virtualized workload.

Abstract: A disclosed method provides a migration service, executable within a hypervisor, configured to calculate, based on a plurality of migration tenets, a migration value for an application running in a VM supported by the hypervisor. If the calculated migration value exceeds a threshold value, a migration tool is invoked to migrate the virtualized application to a functionally equivalent containerized application. The migration value for a VM based application may be determined by calculating a plurality of tenet scores corresponding to a plurality of migration tenets. Each tenant score may equal a sum of scores for each of one or more attributes associated with each tenet. Weightings may be assigned to each tenet such that the migration value is the sum of weighted tenet values. The tenets may include, as non-limiting examples, a security tenet, a density/performance tenet, and a high availability tenet.

Abstract: This on-vehicle control device includes: an acquisition unit configured to acquire a plurality of pieces of wear information regarding a degree of wear of each of a plurality of function units mounted on a vehicle; a selection unit configured to select, on the basis of each piece of the wear information acquired by the acquisition unit, from the plurality of function units, one or a plurality of the function units to be caused to perform a target process that should be performed by one or a plurality of the function units among the plurality of function units; and a control unit configured to perform a control of causing the one or plurality of the function units selected by the selection unit to perform the target process.

Abstract: In a M2M device management system, a Task Orchestration Module, TOM (32) external to the M2M device (20) manages the execution of tasks wholly or partly on the M2M device (20). This alleviates the M2M device (20) of the need to store code, execute tasks, monitor task execution, and the like. The tasks are specified using Finite State Machine, FSM, syntax. A task URL, tURL (34) resource on the M2M device (20) provides a tURL (34) to a resource hosting (36) a service (38) mapping task-IDs to FSM specifications. Communications between the TOM (32) and M2M device (20) is compactly and efficiently achieved using a device management protocol server/client system (16, 18), such as LightWeightM2M (LWM2M). A predetermined mapping (40) at the M2M device (20) maps action labels to library functions (22) of the M2M device (20), obviating the need for code in the M2M device (20) to interpret and execute actions.

Abstract: Disclosed embodiments relate to controlling sets of graphics work (e.g., kicks) assigned to graphics processor circuitry. In some embodiments, tracking slot circuitry implements entries for multiple tracking slots. Slot manager circuitry may store, using an entry of the tracking slot circuitry, software-specified information for a set of graphics work, where the information includes: type of work, dependencies on other sets of graphics work, and location of data for the set of graphics work. The slot manager circuitry may prefetch, from the location and prior to allocating shader core resources for the set of graphics work, configuration register data for the set of graphics work. Control circuitry may program configuration registers for the set of graphics work using the prefetched data and initiate processing of the set of graphics work by the graphics processor circuitry according to the dependencies. Disclosed techniques may reduce kick-to-kick transition time, in some embodiments.

Abstract: An information handling system may include at least one central processing unit (CPU); and a plurality of special-purpose processing units. The information handling system may be configured to: receive information regarding cooling characteristics of the plurality of special-purpose processing units; and assign identification (ID) numbers to each of the plurality of special-purpose processing units in an order that is determined based at least in part on the cooling characteristics.

Abstract: Implementations are disclosed for adaptively reallocating computing resources of resource-constrained devices between tasks performed in situ by those resource-constrained devices. In various implementations, while the resource-constrained device is transported through an agricultural area, computing resource usage of the resource-constrained device ma may be monitored. Additionally, phenotypic output generated by one or more phenotypic tasks performed onboard the resource-constrained device may be monitored. Based on the monitored computing resource usage and the monitored phenotypic output, a state may be generated and processed based on a policy model to generate a probability distribution over a plurality of candidate reallocation actions.

Abstract: A gateway device is connected to a plurality of electronic controllers on-board a vehicle. The gateway device acquires firmware update information, which includes at least a part of updated firmware to be applied to a first electronic controller, patch data, and information indicating where to apply the patch data. When the gateway device determines that the first electronic controller does not include a firmware cache for performing a pre-update firmware cache operation, the gateway device executes a proxy process. In this regard, the gateway device requests the first electronic controller to transmit boot ROM data to the gateway device, merges the patch data and existing firmware to create updated boot ROM data with updated firmware, and transmits the updated boot ROM data to the first electronic controller that updates the boot ROM data and resets the first electronic controller with the updated firmware.

Abstract: A system and method detecting an artificial intelligence (AI) pipeline in a cloud computing environment. The method includes: inspecting a cloud computing environment for an AI pipeline component; detecting a connection between a first AI pipeline component and a second AI pipeline component; generating a representation of each of: the first AI pipeline component, the second AI pipeline component, and the connection, in a security database; and generating an AI pipeline based on the generated representations.

Abstract: Systems and methods presented herein provide examples for distributing resources in a UEM system. In one example, the UEM system can receive a request to check out a user device enrolled in the UEM system. The request can include a profile identifier (“ID”) of a user profile making the request and attributes of the user device. The UEM system can create a hash of group IDs associated with the profile ID. The UEM system can create a device context that includes the device attributes and the hash. The UEM system can then determine if the device context matches to a resource context. Resource contexts can identify a set of UEM resources associated with a device context. Where a match is found, the UEM system can provide the corresponding resources to the user device.

Abstract: A computer system that includes a plurality of compute clusters that are located at different geographical locations. Each compute cluster is powered by a local energy source at a geographical location of that compute cluster. Each local energy source has a pattern of energy supply that is variable over time based on an environmental factor. The computer system further includes a server system that executes a global scheduler that distributes virtual machines that perform compute tasks for server-executed software programs to the plurality of compute clusters of the distributed compute platform. To distribute virtual machines for a target server-executed software program, the global scheduler is configured to select a subset of compute clusters that have different complementary patterns of energy supply such that the subset of compute clusters aggregately provide a target compute resource availability for virtual machines for the target server-executed software program.

Abstract: A method for database management that includes receiving an algorithm from a user. Based on the algorithm, a hierarchical dataflow graph (hDFG) may be generated. The method may further include generating an architecture for a chip based on the hDFG. The architecture for a chip may retrieve a data table from a database. The data table may be associated with the architecture for a chip. Finally, the algorithm may be executed against the data table, such that an action included in the algorithm is performed.